Hierarchical Marine Sensor Network with Dynamic Cluster Head Rotation
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Solution Overview
Problem
Conventional marine data acquisition systems face challenges with high energy consumption, low efficiency, and poor robustness due to multi-hop communication issues, sensor node energy depletion, and inefficient path planning in underwater environments.
Innovation Solution
A hierarchical data acquisition system is implemented, where sensor nodes are arranged in clusters with a cluster head node and ordinary nodes, and an autonomous underwater vehicle uses an improved ant algorithm for path planning considering distance, angle, and pheromone concentration to optimize data transmission, while sensor nodes are dynamically reassigned based on energy levels to balance energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-hop communication is used between sensor nodes and base station, then data transmission is achieved, but data packet loss rate increases and system delay increases
Solution Approach 1:
The patent segments the data transmission path by introducing intermediate relay nodes (surface floating devices and autonomous underwater vehicles) to divide the long multi-hop transmission into shorter segments, reducing packet loss probability at each hop and overall system delay
Solution Approach 2:
The patent introduces surface floating devices and autonomous underwater vehicles as intermediary nodes to facilitate data transmission between deep-sea sensor nodes and the base station, improving transmission reliability by using multiple communication pathways and reducing dependency on single long-hop connections
2Productivity
If all sensor nodes operate as fixed relay nodes at high load, then data transmission capability is maintained, but energy consumption increases and node mortality rate increases
Solution Approach 1:
The patent implements dynamic role assignment where sensor nodes can switch between data collection mode and relay transmission mode based on energy levels and network conditions, allowing the system to adaptively optimize energy consumption while maintaining data acquisition productivity
Solution Approach 2:
The patent introduces mobile relay nodes (autonomous underwater vehicles and surface floating devices) that assume the high-energy-consumption relay function, allowing fixed sensor nodes to operate at lower energy levels while maintaining overall system data transmission capability
3Device complexity
If fixed data transmission link is used, then system structure is simple, but system robustness decreases when node energy consumption causes connection failure
Solution Approach 1:
The patent creates a dynamic network topology where relay nodes can move and reposition themselves to maintain communication links, allowing the system to adapt to node failures and maintain robustness without requiring complex predetermined routing structures
Solution Approach 2:
The patent changes the operational parameters of relay nodes (position, speed, activation state) dynamically in response to network conditions and node energy levels, enabling the system to maintain robustness through parameter adaptation rather than structural complexity
4Device complexity
If conventional ant algorithm is used for AUV path planning, then implementation is simple, but solution efficiency is low and local optimization occurs
Solution Approach 1:
The patent enhances the ant algorithm with feedback mechanisms that evaluate path quality based on multiple criteria (distance, energy consumption, data volume) and use this feedback to guide subsequent ant colony decisions, improving solution efficiency and avoiding local optimization while maintaining reasonable algorithm complexity
5Device complexity
If conventional ant algorithm considers only distance in path planning, then calculation is simple, but AUV energy consumption increases
Solution Approach 1:
The patent extends the path planning optimization from single-parameter (distance) to multi-parameter (distance, energy consumption, data volume) by changing the objective function parameters, enabling the AUV to select paths that minimize overall energy consumption while maintaining reasonable calculation complexity through efficient algorithm design
Data Source
AI summary
A hierarchical data acquisition system and method applied to a marine information network are provided. Multiple sensor nodes are arranged in clusters, each of the clusters includes a cluster head node and multiple ordinary nodes. The multiple ordinary nodes acquire data information of a seafloor and transmit the acquired data information to the cluster head node, and the cluster head node aggregate the data and transmits the aggregated data to an autonomous underwater vehicle, reducing energy consumption of each of the sensor nodes, prolonging service lives of sensors of a data acquisition layer, and improving data acquisition efficiency of a data acquisition layer. In addition, after each of data acquisition periods, a sensor node in each of the clusters is selected as a cluster head node in a next data acquisition cycle. Cluster head nodes are continuously updated in cycles.